Medical image processing device, endoscope system, medical image processing method, and program

ABSTRACT

There are provided a medical image processing device, an endoscope system, a medical image processing method, and a program which detect an optimal lesion region according to an in-vivo position of a captured image. Images at a plurality of in-vivo positions of a subject are acquired from medical equipment that sequentially captures and displays in real time the images; positional information indicating the in-vivo position of the acquired image is acquired; from among a plurality of region-of-interest detection units that detect a region of interest from an input image and correspond to the plurality of in-vivo positions, respectively, a region-of-interest detection unit corresponding to the position indicated by the positional information is selected; and the selected region-of-interest detection unit detects a region of interest from the acquired image.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of and claims prioritybenefit of a prior application Ser. No. 16/905,888, filed on Jun. 18,2020, now allowed. The prior application Ser. No. 16/905,888 is aContinuation of PCT International Application No. PCT/JP2018/045953filed on Dec. 13, 2018 claiming priority under 35 U.S.C § 119(a) toJapanese Patent Application No. 2018-002005 filed on Jan. 10, 2018. Eachof the above applications is hereby expressly incorporated by reference,in its entirety, into the present application.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention relates to a medical image processing device, anendoscope system, a medical image processing method, and a program, andparticularly to a technique of automatically detecting a lesion regionfrom a medical image.

2. Description of the Related Art

In a case where an endoscopic image is captured by an endoscope system,the position (part) in the lumen to be imaged is sequentially changed bythe depth of an endoscope inserted into a living body. Therefore, theendoscope system performs imaging at a plurality of positions in thelumen chronologically from the start to the end of imaging.

JP2011-206251A discloses a technique of acquiring in-vivo positionspecifying information in a case of capturing an endoscopic image andspecifying and displaying an on-model position corresponding to thein-vivo position specifying information, on a part model which is amodel of a part in an object to be examined.

With the technique, it is possible to match the in-vivo position of theendoscope and the position on a guide image with high accuracy.

SUMMARY OF THE INVENTION

Image diagnosis techniques of automatically detecting a lesion regionfrom a medical image have been known. As the automatic detection method,a detection method using the difference between a medical image and apast medical image or the difference between a medical image and astandard image, a method of detecting a lesion region by detecting thematching with a lesion pattern using pattern matching, a method of usinga detector of a learned model in which the features of lesion regionsaccumulated in the past are learned, and the like have been known.

In the lumen imaged by the endoscope system, the structure of the mucousmembrane and the characteristics of the lesion differ depending on theposition thereof. Therefore, in the system of automatically detecting alesion region from an endoscopic image, there is a problem in that it isdifficult to detect an optimal lesion region depending on the imagingposition of the endoscopic image. In addition to the endoscopic image,in a case where a lesion region is automatically detected from an imagecaptured by medical equipment, which sequentially captures images at aplurality of in-vivo positions of a subject, such as an ultrasounddiagnostic apparatus, there is the same problem.

The invention is made in view of such circumstances, and an object ofthe invention is to provide a medical image processing device, anendoscope system, a medical image processing method, and a program whichdetect an optimal lesion region according to an in-vivo position of acaptured image.

An aspect of a medical image processing device for achieving the objectis a medical image processing device comprising an image acquisitionunit that acquires images at a plurality of in-vivo positions of asubject, from medical equipment that sequentially captures and displaysin real time the images; a positional information acquisition unit thatacquires positional information indicating the in-vivo position of theacquired image; a plurality of region-of-interest detection units whichdetect a region of interest from an input image and correspond to theplurality of in-vivo positions, respectively; a selection unit thatselects a region-of-interest detection unit corresponding to theposition indicated by the positional information from among theplurality of region-of-interest detection units; and a control unit thatcauses the selected region-of-interest detection unit to detect a regionof interest from the acquired image.

According to the aspect, the positional information indicating thein-vivo position of the image is acquired, the image being acquired fromthe medical equipment which sequentially captures and displays in realtime the images at the plurality of in-vivo positions of the subject;from among the plurality of region-of-interest detection units thatdetect a region of interest from the input image and correspond to theplurality of in-vivo positions, respectively, a region-of-interestdetection unit corresponding to the position indicated by the positionalinformation is selected; and a region of interest is detected from theacquired image by the selected region-of-interest detection unit.Therefore, it is possible to detect an optimal lesion region accordingto the in-vivo position of the acquired image.

It is preferable that the image acquisition unit sequentially acquires aplurality of in-vivo images obtained by chronological imaging. In thismanner, it is possible to detect an optimal lesion region according tothe in-vivo position of the plurality of in-vivo images obtained bychronological imaging.

Further, it is preferable that the image acquisition unit sequentiallyacquires a plurality of images captured at a fixed frame rate. In thismanner, it is possible to detect an optimal lesion region according tothe in-vivo position of the plurality of images captured at a fixedframe rate.

It is preferable that the plurality of region-of-interest detectionunits are a plurality of learned models. In this manner, it is possibleto appropriately detect a lesion region.

It is preferable that the plurality of learned models are models learnedusing different data sets, respectively. In this manner, it is possibleto perform different detection.

It is preferable that the plurality of learned models are models learnedusing data sets consisting of images captured at different in-vivopositions, respectively. In this manner, it is possible to detect alesion region according to the in-vivo position of the image.

It is preferable that the positional information acquisition unitcomprises a position recognition unit that recognizes an in-vivoposition from the acquired image. In this manner, it is possible toappropriately recognize the in-vivo position of the image.

Further, the positional information acquisition unit may comprise aninput unit that receives the positional information through a user'sinput. In this manner, it is possible to appropriately recognize thein-vivo position of the image.

It is preferable that the medical image processing device furthercomprises a display control unit that causes the medical equipment todisplay the position indicated by the acquired positional information.In this manner, it is possible for the doctor to know that the positionis appropriately recognized.

It is preferable that the medical equipment comprises an ultrasoundprobe that transmits ultrasonic waves toward an inside of the subjectfrom an outside of the subject, and receives the ultrasonic wavesreflected from the inside of the subject, an ultrasound image generationunit that generates an ultrasound image using the ultrasonic wavesreceived by the ultrasound probe, and a display unit that displays theultrasound image. In this manner, it is possible to detect an optimallesion region according to the in-vivo position of the ultrasound imagegenerated by the ultrasound diagnostic apparatus.

It is preferable that the medical equipment comprises an endoscope to beinserted into a body cavity of the subject, a camera that images thebody cavity, and a display unit that displays the captured image. Inthis manner, it is possible to detect an optimal lesion region accordingto the in-vivo position of the endoscopic image generated by theendoscope system.

An aspect of an endoscope system for achieving the object is anendoscope system comprising medical equipment that has an endoscope tobe inserted into a body cavity of a subject, a camera that images thebody cavity, and a display unit that displays the captured image; and amedical image processing device having an image acquisition unit thatacquires images at a plurality of in-vivo positions of a subject, frommedical equipment that sequentially captures and displays in real timethe images; a positional information acquisition unit that acquirespositional information indicating the in-vivo position of the acquiredimage; a plurality of region-of-interest detection units which detect aregion of interest from an input image and correspond to the pluralityof in-vivo positions, respectively; a selection unit that selects aregion-of-interest detection unit corresponding to the positionindicated by the positional information from among the plurality ofregion-of-interest detection units; and a control unit that causes theselected region-of-interest detection unit to detect a region ofinterest from the acquired image.

According to the aspect, the image is acquired from the medicalequipment which has an endoscope to be inserted into a body cavity of asubject, a camera that images the body cavity, and a display unit thatdisplays the captured image and which sequentially captures the imagesat the plurality of in-vivo positions of the subject; the positionalinformation indicating the in-vivo position of the image is acquired;from among the plurality of region-of-interest detection units thatdetect a region of interest from the input image and correspond to theplurality of in-vivo positions, respectively, a region-of-interestdetection unit corresponding to the position indicated by the positionalinformation is selected; and a region of interest is detected from theacquired image by the selected region-of-interest detection unit.Therefore, it is possible to detect an optimal lesion region accordingto the in-vivo position of the acquired image.

An aspect of a medical image processing method for achieving the objectis a medical image processing method comprising an image acquisitionstep of acquiring images at a plurality of in-vivo positions of asubject, from medical equipment that sequentially captures and displaysin real time the images; a positional information acquisition step ofacquiring positional information indicating the in-vivo position of theacquired image; a plurality of region-of-interest detection steps ofdetecting a region of interest from an input image, the plurality ofregion-of-interest detection steps corresponding to the plurality ofin-vivo positions, respectively; a selection step of selecting aregion-of-interest detection step corresponding to the positionindicated by the positional information from among the plurality ofregion-of-interest detection steps; and a control step of causing theselected region-of-interest detection step to detect a region ofinterest from the acquired image.

According to the aspect, the positional information indicating thein-vivo position of the image is acquired, the image being acquired fromthe medical equipment which sequentially captures and displays in realtime the images at the plurality of in-vivo positions of the subject;from among the plurality of region-of-interest detection steps thatdetect a region of interest from the input image and correspond to theplurality of in-vivo positions, respectively, a region-of-interestdetection step corresponding to the position indicated by the positionalinformation is selected; and a region of interest is detected from theacquired image by the selected region-of-interest detection step.Therefore, it is possible to detect an optimal lesion region accordingto the in-vivo position of the acquired image.

An aspect of a program for execution of a computer for achieving theobject is a program causing a computer to execute an image acquisitionstep of acquiring images at a plurality of in-vivo positions of asubject, from medical equipment that sequentially captures and displaysin real time the images; a positional information acquisition step ofacquiring positional information indicating the in-vivo position of theacquired image; a plurality of region-of-interest detection steps ofdetecting a region of interest from an input image, the plurality ofregion-of-interest detection steps corresponding to the plurality ofin-vivo positions, respectively; a selection step of selecting aregion-of-interest detection step corresponding to the positionindicated by the positional information from among the plurality ofregion-of-interest detection steps; and a control step of causing theselected region-of-interest detection step to detect a region ofinterest from the acquired image.

According to the aspect, the positional information indicating thein-vivo position of the image is acquired, the image being acquired fromthe medical equipment which sequentially captures the images at theplurality of in-vivo positions of the subject; from among the pluralityof region-of-interest detection steps that detect a region of interestfrom the input image and correspond to the plurality of in-vivopositions, respectively, a region-of-interest detection stepcorresponding to the position indicated by the positional information isselected; and a region of interest is detected from the acquired imageby the selected region-of-interest detection step. Therefore, it ispossible to detect an optimal lesion region according to the in-vivoposition of the acquired image.

According to the invention, it is possible to detect an optimal lesionregion according to an in-vivo position of a captured image.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an external view illustrating an endoscope system.

FIG. 2 is a block diagram illustrating functions of the endoscopesystem.

FIG. 3 is a graph illustrating an intensity distribution of light.

FIG. 4 is a flowchart illustrating processing of an image diagnosismethod by an endoscope system 10.

FIG. 5 is a diagram illustrating an example of a display unit in which acaptured image and acquired positional information.

FIG. 6 is a diagram illustrating an example of a display unit in which acaptured image and acquired positional information.

FIG. 7 is a block diagram illustrating functions of the endoscopesystem.

FIG. 8 is a block diagram illustrating functions of an ultrasounddiagnostic apparatus.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

Hereinafter, preferred embodiments of the invention will be described indetail with reference to the accompanying drawings.

First Embodiment

[Configuration of Endoscope System]

FIG. 1 is an external view illustrating an endoscope system 10 (anexample of medical equipment) according to a first embodiment. Asillustrated in FIG. 1 , the endoscope system 10 comprises an endoscope12, a light source device 14, a processor device 16, a display unit 18,and an input unit 20.

In the embodiment, the endoscope 12 is a lower endoscope which isinserted from the anus of a subject and is used for observation of therectum, the large intestine, and the like. The endoscope 12 is opticallyconnected to the light source device 14. Further, the endoscope 12 iselectrically connected to the processor device 16.

The endoscope 12 has an insertion part 12A that is to be inserted into abody cavity of a subject, an operation part 12B provided in a proximalend portion of the insertion part 12A, and a bendable part 12C and adistal end part 12D that are provided on the distal end side of theinsertion part 12A.

An angle knob 12E and a mode switching switch 13 is provided in theoperation part 12B.

The bendable part 12C is bent by operating the angle knob 12E. Thedistal end part 12D is directed in a desired direction by the bendingoperation.

The mode switching switch 13 is used in an operation of switchingobservation modes. The endoscope system 10 has a plurality ofobservation modes with different wavelength patterns of irradiationlight. A doctor can set a desired observation mode by operating the modeswitching switch 13. In the endoscope system 10, an image according tothe set observation mode is generated by a combination of the wavelengthpattern and the image processing and is displayed on the display unit18.

Further, an acquisition instruction input unit (not illustrated) isprovided to the operation part 12B. The acquisition instruction inputunit is an interface for the doctor to input a static image acquisitioninstruction. The acquisition instruction input unit receives the staticimage acquisition instruction. The static image acquisition instructionreceived by the acquisition instruction input unit is input to theprocessor device 16.

The processor device 16 is electrically connected to the display unit 18and the input unit 20. The display unit 18 is a display device thatoutputs and displays an image of an observation target and informationassociated with the image of the observation target. The input unit 20functions as a user interface for receiving input operations such asvarious instructions and function setting of the endoscope system 10.

FIG. 2 is a block diagram illustrating functions of the endoscope system10. As illustrated in FIG. 2 , the light source device 14 comprises afirst laser light source 22A, a second laser light source 22B, and alight source control unit 24.

The first laser light source 22A is a blue laser light source having acenter wavelength of 445 nm. The second laser light source 22B is aviolet laser light source having a center wavelength of 405 nm. As thefirst laser light source 22A and the second laser light source 22B, alaser diode can be used. Emission of the first laser light source 22Aand emission of the second laser light source 22B are individuallycontrolled by the light source control unit 24. The emission intensityratio of the first laser light source 22A and the second laser lightsource 22B is freely changed.

As illustrated in FIG. 2 , the endoscope 12 comprises an optical fiber28A, an optical fiber 28B, a phosphor 30, a diffusion member 32, animaging lens 34, an imaging element 36, and an analog-to-digitalconversion unit 38.

An irradiation unit is constituted by the first laser light source 22A,the second laser light source 22B, the optical fiber 28A, the opticalfiber 28B, the phosphor 30, and the diffusion member 32.

Laser light emitted from the first laser light source 22A is emitted tothe phosphor 30 disposed on the distal end part 12D of the endoscope 12by the optical fiber 28A. The phosphor 30 is configured to include aplurality of kinds of phosphors that absorb some of blue laser lightfrom the first laser light source 22A to emit green to yellow excitationlight. In this manner, light emitted from the phosphor 30 becomes white(quasi white) light L₁ in which green to yellow excitation light L₁₁ asexcitation light of the blue laser light from the first laser lightsource 22A and blue laser light L₁₂ transmitted through the phosphor 30without being absorbed to the phosphor 30 are combined.

Here, the white light is not limited to light that strictly includes allwavelength components of visible light. For example, the white light ispreferably light including light in a specific wavelength range forexample, R, G, and B, and broadly includes light including wavelengthcomponents from green to red, or light including wavelength componentsfrom blue to green.

On the other hand, laser light emitted from the second laser lightsource 22B is emitted to the diffusion member 32 disposed on the distalend part 12D of the endoscope 12 by the optical fiber 28B. As thediffusion member 32, a resin material having transmittance or the likecan be used. Light emitted from the diffusion member 32 becomes light L₂having a narrow-band wavelength with uniform light intensity in anirradiation region.

FIG. 3 is a graph illustrating an intensity distribution of light L₁ andlight L₂. The light source control unit 24 (an example of wavelengthpattern change unit) changes a light intensity ratio of the first laserlight source 22A and the second laser light source 22B. In this manner,the light intensity ratio of the light L₁ and the light L₂ is changed,and the wavelength pattern of irradiation light L₀ as synthesis light ofthe light L₁ and the light L₂ is changed. Therefore, it is possible toemit irradiation light L₀ with the different wavelength patternaccording to the observation mode.

Returning to the description of FIG. 2 , an imaging unit (camera) isconstituted by the imaging lens 34, the imaging element 36, and theanalog-to-digital conversion unit 38. The imaging unit is disposed onthe distal end part 12D of the endoscope 12.

The imaging lens 34 causes incident light to be formed on the imagingelement 36. The imaging element 36 generates an analog signal accordingto the received light. As the imaging element 36, a charge coupleddevice (CCD) image sensor, or a complementary metal oxide semiconductor(CMOS) image sensor is used. The analog signal output from the imagingelement 36 is converted into a digital signal by the analog-to-digitalconversion unit 38, and is input to the processor device 16.

Further, as illustrated in FIG. 2 , the processor device 16 comprises animaging control unit 40, an image processing unit 42, an imageacquisition unit 44, a lesion region detection unit 46, a positionalinformation acquisition unit 48, a selection unit 52, a lesion regiondetection control unit 54, a display control unit 58, a storage controlunit 60, and a storage unit 62.

The imaging control unit 40 generally controls imaging of a video and astatic image by the endoscope system 10 by controlling the light sourcecontrol unit 24 of the light source device 14, the imaging element 36and the analog-to-digital conversion unit 38 of the endoscope 12, andthe image processing unit 42 of the processor device 16.

The image processing unit 42 performs image processing on the digitalsignal input from the analog-to-digital conversion unit 38 of theendoscope 12 and generates image data indicating an image (hereinafter,referred to as an image). The image processing unit 42 performs imageprocessing according to the wavelength pattern of irradiation light in acase of imaging.

The image acquisition unit 44 acquires the image generated by the imageprocessing unit 42. That is, the image acquisition unit 44 sequentiallyacquires a plurality of images obtained by chronologically imaging thebody cavity of a subject (an example of a living body) at a fixed framerate. The image acquisition unit 44 may acquire an image input from theinput unit 20 or an image stored in the storage unit 62. Further, animage may be acquired from an external device such as a server connectedto a network (not illustrated). The images in such a case are preferablya plurality of images captured chronologically.

The lesion region detection unit 46 detects a lesion region from theinput image (input image). The lesion region detection unit 46 comprisesa first detection unit 46A, a second detection unit 46B, a thirddetection unit 46C, a fourth detection unit 46D, a fifth detection unit46E, a sixth detection unit 46F, a seventh detection unit 46G, and aneighth detection unit 46H (an example of a plurality ofregion-of-interest detection units) respectively corresponding to aplurality of positions in the cavity. Here, as an example, the firstdetection unit 46A corresponds to the rectum, the second detection unit46B corresponds to the sigmoid colon, the third detection unit 46Ccorresponds to the descending colon, the fourth detection unit 46Dcorresponds to the transverse colon, the fifth detection unit 46Ecorresponds to the ascending colon, the sixth detection unit 46Fcorresponds to the cecum, the seventh detection unit 46G corresponds tothe ileum, and the eighth detection unit 46H corresponds to the jejunum(an example of a plurality of region-of-interest detection steps).

Each of the first detection unit 46A, the second detection unit 46B, thethird detection unit 46C, the fourth detection unit 46D, the fifthdetection unit 46E, the sixth detection unit 46F, the seventh detectionunit 46G, and the eighth detection unit 46H is a learned model. Theplurality of learned models are models learned using different datasets, respectively. Specifically, the plurality of learned models aremodels learned using data sets consisting of images captured atdifferent positions in the body cavity, respectively.

That is, the first detection unit 46A is a model learned using a dataset consisting of images of the rectum, the second detection unit 46B isa model learned using a data set consisting of images of the sigmoidcolon, the third detection unit 46C is a model learned using a data setconsisting of images of the descending colon, the fourth detection unit46D is a model learned using a data set consisting of images of thetransverse colon, the fifth detection unit 46E is a model learned usinga data set consisting of images of the ascending colon, the sixthdetection unit 46F is a model learned using a data set consisting ofimages of the cecum, the seventh detection unit 46G is a model learnedusing a data set consisting of images of the ileum, and the eighthdetection unit 46H is a model learned using a data set consisting ofimages of the jejunum.

It is preferable that these learned models use a support vector machine,or a convolutional neural network.

The positional information acquisition unit 48 acquires positionalinformation I indicating the position of the image in the body cavity,the image being acquired by the image acquisition unit 44. Here, thedoctor inputs the positional information I using the input unit 20. Thepositional information acquisition unit 48 acquires the positionalinformation I input from the input unit 20.

As the positional information I indicating the position of the image inthe body cavity, the rectum, the sigmoid colon, the descending colon,the transverse colon, the ascending colon, the cecum, the ileum, thejejunum, and the like are input. A configuration in which these positioncandidates are displayed in a selectable manner on the display unit 18and the doctor selects the position using the input unit 20 may beadopted.

The selection unit 52 selects a detection unit corresponding to theposition that the positional information I acquired by the positionalinformation acquisition unit 48 indicates, from the lesion regiondetection unit 46. That is, the selection unit 52 selects the firstdetection unit 46A in a case where the position indicated by thepositional information I is the rectum, the second detection unit 46B ina case where the position indicated by the positional information I isthe sigmoid colon, the third detection unit 46C in a case where theposition indicated by the positional information I is the descendingcolon, the fourth detection unit 46D in a case where the positionindicated by the positional information I is the transverse colon, thefifth detection unit 46E in a case where the position indicated by thepositional information I is the ascending colon, the sixth detectionunit 46F in a case where the position indicated by the positionalinformation I is the cecum, the seventh detection unit 46G in a casewhere the position indicated by the positional information I is theileum, and the eighth detection unit 46H in a case where the positionindicated by the positional information I is the jejunum.

The lesion region detection control unit 54 (an example of a controlunit) causes the detection unit selected by the selection unit 52 todetect a lesion region (an example of a region of interest) from theimage acquired by the image acquisition unit 44. Here, the lesion regionis not limited to a region caused by disease, and includes a region in astate different from a normal state in appearance. Examples of thelesion region include polyps, cancers, colonic diverticulum,inflammation, treatment scars such as endoscopic mucosal resection (EMR)scars or endoscopic submucosal dissection (ESD) scars, clip locations,bleeding points, perforations, and vascular atypia.

A medical image processing device 56 is constituted by the imageacquisition unit 44, the lesion region detection unit 46, the positionalinformation acquisition unit 48, the selection unit 52, and the lesionregion detection control unit 54.

The display control unit 58 causes the display unit 18 to display animage generated by the image processing unit 42. Further, the positionalinformation I (the position indicated by the positional information I)acquired by the positional information acquisition unit 48 is displayed.Furthermore, the lesion region detected by the lesion region detectionunit 46 is superimposed and displayed on the image in a recognizablemanner.

The storage control unit 60 causes the storage unit 62 to store theimage generated by the image processing unit 42. For example, the imagecaptured according to the static image acquisition instruction, and theinformation of the wavelength pattern of the irradiation light L0 in acase of capturing the image are stored in the storage unit 62.

The storage unit 62 is a storage device such as a hard disk. The storageunit 62 is not limited to a device built in the processor device 16. Forexample, the storage unit 62 may be an external storage device (notillustrated) connected to the processor device 16. The external storagedevice may be connected via a network (not illustrated).

The endoscope system 10 configured in this manner usually performscapturing of a video at a fixed frame rate, and causes the display unit18 to display the captured image and the positional information I of theimage. Further, a lesion region is detected from the captured video, andthe detected lesion region is superimposed and displayed on the video ina recognizable manner on the display unit 18.

[Operation Method of Endoscope System]

FIG. 4 is a flowchart illustrating processing of an image diagnosismethod by the endoscope system 10 (an example of a medical imageprocessing method and an operation method of the endoscope system).

In starting image diagnosis by the endoscope system 10, in step S1 (anexample of an image acquisition step), imaging and displaying of a videoare performed under the control of the imaging control unit 40. That is,the light source control unit 24 sets light emitted from the first laserlight source 22A and light emitted from the second laser light source22B to a light intensity ratio corresponding to a desired observationmode. In this manner, irradiation light L₀ with a desired wavelengthpattern is emitted to the part to be observed in the body cavity of thesubject.

Further, the imaging control unit 40 controls the imaging element 36,the analog-to-digital conversion unit 38, and the image processing unit42, and captures an image of the part to be observed by receiving thereflected light from the part to be observed. The image acquisition unit44 acquires the captured image.

In this manner, the endoscope system 10 captures an image (video) at afixed frame rate.

Next, in step S2 (an example of a positional information acquisitionstep), the positional information I is acquired by the positionalinformation acquisition unit 48. Here, the doctor inputs positionalinformation I indicating the position of the image in the lumen usingthe input unit 20, the image being captured in step S1. The positionalinformation acquisition unit 48 acquires the positional information Iinput from the input unit 20. The doctor may input the positionalinformation I before capturing the image.

In a case where the positional information I is newly input from theinput unit 20, the positional information I, which is input last, isacquired as the current positional information I. It is sufficient thatthe doctor inputs the positional information I using the input unit 20only in a case where the imaging position (part) of the endoscope 12 ischanged.

Next, in step S3 (an example of a selection step), the selection unit 52selects any detection unit among the first detection unit 46A to theeighth detection unit 46H on the basis of the positional information Iacquired in step S2. That is, the first detection unit 46A is selectedin a case where the position in the lumen indicated by the positionalinformation I is the rectum, the second detection unit 46B is selectedin a case where the position in the lumen indicated by the positionalinformation I is the sigmoid colon, the third detection unit 46C isselected in a case where the position in the lumen indicated by thepositional information I is the descending colon, the fourth detectionunit 46D is selected in a case where the position in the lumen indicatedby the positional information I is the transverse colon, the fifthdetection unit 46E is selected in a case where the position in the lumenindicated by the positional information I is the ascending colon, thesixth detection unit 46F is selected in a case where the position in thelumen indicated by the positional information I is the cecum, theseventh detection unit 46G is selected in a case where the position inthe lumen indicated by the positional information I is the ileum, andthe eighth detection unit 46H is selected in a case where the positionin the lumen indicated by the positional information I is the jejunum.

Next, in step S4 (an example of a control step), the lesion regiondetection control unit 54 causes the selected detection unit (an exampleof the selected region-of-interest detection step) to detect a lesionregion from the image acquired by the image acquisition unit 44. Forexample, in a case where the first detection unit 46A is selected, thefirst detection unit 46A detects a lesion region from the image.Further, in a case where the second detection unit 46B is selected, thesecond detection unit 46B detects a lesion region from the image.

The first detection unit 46A to the eighth detection unit 46H haveperformed learning according to the positions (parts) in the lumen,respectively. Therefore, it is possible to perform appropriate detectionby causing a detection unit according to the acquired positionalinformation I to detect a lesion region.

In step S5, the display control unit 58 causes the display unit 18 todisplay in real time the image captured in step S1. The display in realtime is processing of updating and displaying at any time the imagesequentially captured, and includes the display including a time lagsuch as time required for the image processing and time required forcommunication to the display unit 18.

Further, the display control unit 58 causes the display unit 18 todisplay the positional information I acquired in step S3.

In a case where a lesion region is detected in step S4, the displaycontrol unit 58 causes the display unit 18 to superimpose and displaythe detected lesion region on the displayed image in a recognizablemanner.

FIGS. 5 and 6 are diagrams illustrating an example of the display unit18 in which a captured image G_(E) and acquired positional informationI. In the example illustrated in FIG. 5 , as the positional informationI, characters “Rectum” corresponding to the position indicated by thepositional information I are displayed together with the image G_(E).Here, the positional information I is displayed in English on the upperright of the image, but the display position and the language are notlimited to this example.

Further, in case illustrated in FIG. 6 , as the positional informationI, a schematic diagram G_(S) of the lumen is displayed on the displayunit 18 together with the image G_(E), and a circle is displayed at theposition indicated by the positional information I on the schematicdiagram G_(S). Here, a circle is used as a figure, but the shape andcolor are not limited thereto, and it is sufficient that the figure isdisplayed such that the doctor recognizes the position.

It is possible for the doctor to check that the positional information Iis correctly set, by displaying the positional information I.

The storage control unit 60 causes the storage unit 62 to store theimage G_(E). Further, the image G_(E) and the positional information Iof the image G_(E) may be associated and stored in the storage unit 62.

Finally, in step S6, it is determined whether the image diagnosis by theendoscope system 10 is to be ended. The doctor can input an endinstruction of the imaging operation of the endoscope system 10, usingthe input unit 20.

In a case where an end instruction is input, the processing of thepresent flowchart is ended. In a case where an end instruction is notinput, the processing returns to step S1, and imaging is continued.

In this manner, it is possible to improve the accuracy of detecting alesion region by acquiring the positional information I and detectingthe lesion region by the detection unit according to the positionalinformation I.

Here, the endoscope system 10 acquires the positional information I bythe doctor's input using the input unit 20, but the endoscope system 10may acquire shape information of the bendable part 12C of the endoscope12 by an endoscope insertion shape observation device (not illustrated)using a magnetic coil or the like, and may estimate the positionalinformation I of the distal end part 12D from the shape information.Further, the subject is irradiated with X-rays from the outside toacquire the shape information of the bendable part 12C of the endoscope12, and the positional information I of the distal end part 12D may beestimated from the shape information.

Here, an example in which the invention is applied to the lowerendoscope has been described, but the invention can be applied to anupper endoscope which is inserted from the mouth or nose of the subjectand is used for observation of the esophagus, stomach, and the like. Inthis case, as the positional information I indicating the position ofthe image in the body cavity, the pharynx, the esophagus, the stomach,the duodenum, and the like are input using the input unit 20. Further,the lesion region detection unit 46 may comprise detection units thatdetect lesion regions of the pharynx, the esophagus, the stomach, theduodenum, and the like, respectively.

Here, the lesion region detection unit 46 comprises a plurality ofdetection units, but the lesion region detection unit 46 may compriseone detection unit and may switch data or parameters to be used for eachposition. For example, the lesion region detection unit 46 comprisesonly the first detection unit 46A, and a parameter according to theacquired positional information I is set to the first detection unit46A. The first detection unit 46A detects a lesion region by using theset parameter.

With such a configuration, it is possible to improve the accuracy ofdetecting a lesion region by detecting the lesion region by thedetection unit according to the positional information I.

Second Embodiment

The positional information I is not limited to an aspect input from theoutside of the endoscope system 10. For example, estimation can beperformed from the captured image.

FIG. 7 is a block diagram illustrating functions of an endoscope system70. Parts common with the block diagram illustrated in FIG. 2 are giventhe same reference numerals, and the detailed description thereof willbe omitted.

The endoscope system 70 comprises a position recognition unit 50 in thepositional information acquisition unit 48. In the embodiment, the imageacquired by the image acquisition unit 44 is input to the positionalinformation acquisition unit 48. The position recognition unit 50recognizes (estimates) the imaged position (part) in the lumen from theimage feature quantity of the input image.

For example, the position recognition unit 50 is a learned model inwhich images of the mucous membrane of each position are learned by amachine learning algorithm such as deep learning.

In this manner, in the endoscope system 70, it is possible to acquirethe positional information I by analyzing the image in the positionrecognition unit 50.

The selection unit 52 selects any detection unit among the firstdetection unit 46A, the second detection unit 46B, the third detectionunit 46C, the fourth detection unit 46D, the fifth detection unit 46E,the sixth detection unit 46F, the seventh detection unit 46G, and theeighth detection unit 46H on the basis of the acquired positionalinformation I.

The lesion region detection control unit 54 causes the selecteddetection unit to detect a lesion region from the image acquired by theimage acquisition unit 44.

With this configuration, it is possible to immediately acquire thepositional information I in a case where the position of the distal endpart 12D of the endoscope 12 is changed. In this manner, it is possibleto improve the accuracy of detecting a lesion region.

Further, similar to the first embodiment, the display control unit 58causes the display unit 18 to display the positional information I. Itis possible for the doctor to check that the positional information I iscorrectly recognized, by displaying the positional information I. Aconfiguration in which the positional information I can be correctedusing the input unit 20 in a case where the displayed positionalinformation I is not correct may be adopted.

The position recognition unit 50 may detect a characteristic landmark ofeach position, and may estimate the position from information of thedetected landmark. For example, the position is estimated to be theduodenum in a case where the bile is detected as the landmark, theposition is estimated to be the ileum or jejunum in a case where thevillus is detected, and the position is estimated to be the cecum orascending colon in a case where ileocecal valve is detected.

In case of the upper endoscope, in a case where the vocal cords orepiglottis is detected as the landmark, the position can be estimated tobe the pharynx, and in a case where the squamous epithelium is detected,the position can be estimated to be the esophagus.

Third Embodiment

As medical equipment that sequentially captures images at a plurality ofin-vivo positions of a subject, there is an ultrasound diagnosticapparatus that generates an ultrasound image. Here, an example in whichthe invention is applied to the ultrasound diagnostic apparatus will bedescribed.

FIG. 8 is a block diagram illustrating functions of an ultrasounddiagnostic apparatus 100. As illustrated in FIG. 8 , the ultrasounddiagnostic apparatus 100 comprises the display unit 18, the input unit20, the medical image processing device 56, the display control unit 58,the storage control unit 60, the storage unit 62, an ultrasound probe102, a transmission/reception control unit 104, a transmission unit 106,a reception unit 108, and an image processing unit 110.

In some cases, the apparatus without the ultrasound probe 102 may bereferred to as the ultrasound diagnostic apparatus. In this case, theultrasound diagnostic apparatus is connected to the ultrasound probe.

The ultrasound probe 102 transmits ultrasonic waves toward the livingbody from the outside of the subject, and receives the ultrasonic wavesreflected from the living body of the subject.

The ultrasound probe 102 is connected to the transmission unit 106 andthe reception unit 108. The transmission unit 106 and the reception unit108 perform transmission and reception of ultrasonic waves using theultrasound probe 102 under the control of the transmission/receptioncontrol unit 104.

The transmission unit 106 outputs a transmission signal to an ultrasonictransducer (not illustrated) that the ultrasound probe 102 comprises.The ultrasonic transducer of the ultrasound probe 102 transmits theultrasonic waves according to the transmission signal, to the subject.

Further, the ultrasonic waves reflected from the living body of thesubject are received by the ultrasonic transducer that has transmittedthe ultrasonic waves. The ultrasonic transducer outputs a reflected wavesignal to the reception unit 108. The reception unit 108 receives thereflected wave signal. Furthermore, the reception unit 108 performsamplification processing, analog-to-digital conversion processing, andthe like on the reflected wave signal, and outputs a digital signal tothe image processing unit 110.

The image processing unit 110 (an example of an ultrasound imagegeneration unit) performs image processing on the digital signal inputfrom the reception unit 108 to generate an ultrasound image signal.

The configurations of the display unit 18, the input unit 20, themedical image processing device 56, the display control unit 58, thestorage control unit 60, and the storage unit 62 are the same as thoseof the endoscope system 10 according to the first embodiment.

The positional information acquisition unit 48 that the medical imageprocessing device 56 comprises acquires the liver, the gallbladder, thepancreas, the spleen, the kidney, the uterus, the ovary, the prostate,and the like as the positional information I.

Further, in the lesion region detection unit 46 that the medical imageprocessing device 56 comprises, the first detection unit 46A detects alesion region of the liver, the second detection unit 46B detects alesion region of the gallbladder, the third detection unit 46C detects alesion region of the pancreas, the fourth detection unit 46D detects alesion region of the spleen, the fifth detection unit 46E detects alesion region of the kidney, the sixth detection unit 46F detects alesion region of the uterus, the seventh detection unit 46G detects alesion region of the ovary, and the eighth detection unit 46H detects alesion region of the prostate.

That is, here, the first detection unit 46A is a learned model learnedusing a data set consisting of images of the liver, the second detectionunit 46B is a learned model learned using a data set consisting ofimages of the gallbladder, the third detection unit 46C is a learnedmodel learned using a data set consisting of images of the pancreas, thefourth detection unit 46D is a learned model learned using a data setconsisting of images of the spleen, the fifth detection unit 46E is alearned model learned using a data set consisting of images of thekidney, the sixth detection unit 46F is a learned model learned using adata set consisting of images of the uterus, the seventh detection unit46G is a learned model learned using a data set consisting of images ofthe ovary, and the eighth detection unit 46H is a learned model learnedusing a data set consisting of images of the prostate.

The processing of the image diagnosis method by the ultrasounddiagnostic apparatus 100 is the same as the flowchart illustrated inFIG. 4 .

That is, transmission and reception of ultrasonic waves are performedwith respect to the subject using the ultrasound probe, and theultrasound image signal is generated by the image processing unit 110(step S1). This operation is performed at a fixed frame rate. Further,the positional information I regarding the position where the ultrasoundimage is captured is acquired by the doctor's input using the input unit20 or the like (step S2).

The selection unit 52 selects any detection unit among the firstdetection unit 46A, the second detection unit 46B, the third detectionunit 46C, the fourth detection unit 46D, the fifth detection unit 46E,the sixth detection unit 46F, the seventh detection unit 46G, and theeighth detection unit 46H on the basis of the positional information I(step S3). That is, the first detection unit 46A is selected in a casewhere the in-vivo position of the subject indicated by the positionalinformation I is the liver, the second detection unit 46B is selected ina case where the in-vivo position of the subject indicated by thepositional information I is the gallbladder, the third detection unit46C is selected in a case where the in-vivo position of the subjectindicated by the positional information I is the pancreas, the fourthdetection unit 46D is selected in a case where the in-vivo position ofthe subject indicated by the positional information I is the spleen, thefifth detection unit 46E is selected in a case where the in-vivoposition of the subject indicated by the positional information I is thekidney, the sixth detection unit 46F is selected in a case where thein-vivo position of the subject indicated by the positional informationI is the uterus, the seventh detection unit 46G is selected in a casewhere the in-vivo position of the subject indicated by the positionalinformation I is the ovary, and the eighth detection unit 46H isselected in a case where the in-vivo position of the subject indicatedby the positional information I is the prostate.

The lesion region detection control unit 54 causes the selecteddetection unit to detect a lesion region from the image acquired by theimage acquisition unit 44 (step S4).

The display control unit 58 causes the display unit 18 to display inreal time the image captured in step S1. Further, the display unit 18displays the positional information I (step S5). In a case where alesion region is detected in step S4, the detected lesion region issuperimposed and displayed on the image displayed on the display unit 18in a recognizable manner.

Until it is determined in step S6 that the image diagnosis by theultrasound diagnostic apparatus 100 is to be ended, the above operationis repeated.

As described above, also in the ultrasound diagnostic apparatus, it ispossible to improve the accuracy of detecting a lesion region byacquiring the positional information I and detecting the lesion regionby the detection unit according to the positional information I.

Additional Remarks

Configurations to be described below are also included in the scope ofthe invention in addition to the above-described aspects and examples.

(Additional Remark 1)

A medical image processing device comprising: a medical image analysisprocessing unit that detects a region of interest, which is a region tobe noticed, on the basis of a feature quantity of pixels of a medicalimage; and a medical image analysis result acquisition unit thatacquires an analysis result of the medical image analysis processingunit.

(Additional Remark 2)

The medical image processing device comprising: a medical image analysisprocessing unit that detects presence or absence of an object to benoticed, on the basis of a feature quantity of pixels of a medicalimage; and a medical image analysis result acquisition unit thatacquires an analysis result of the medical image analysis processingunit.

(Additional Remark 3)

The medical image processing device, wherein the medical image analysisresult acquisition unit acquires the analysis result of the medicalimage from a recording device, and the analysis result includes any oneor both of the region of interest that is the region to be noticedincluded in the medical image and presence or absence of the object tobe noticed.

(Additional Remark 4)

The medical image processing device, wherein the medical image is anormal light image that is obtained from the application of light in awhite-light wavelength range or light in a plurality of wavelengthranges as the light in a white-light wavelength range.

(Additional Remark 5)

The medical image processing device, wherein the medical image is animage that is obtained from the application of light in a specificwavelength range, and the specific wavelength range is a range narrowerthan the white-light wavelength range.

(Additional Remark 6)

The medical image processing device, wherein the specific wavelengthrange is a blue-light wavelength range or a green-light wavelength rangeof a visible-light wavelength range.

(Additional Remark 7)

The medical image processing device, wherein the specific wavelengthrange includes a wavelength range of 390 nm to 450 nm or 530 nm to 550nm, and light in the specific wavelength range has a peak wavelength ina wavelength range of 390 nm to 450 nm or 530 nm to 550 nm.

(Additional Remark 8)

The medical image processing device, wherein the specific wavelengthrange is a red-light wavelength range of a visible-light wavelengthrange.

(Additional Remark 9)

The medical image processing device, wherein the specific wavelengthrange includes a wavelength range of 585 nm to 615 nm or 610 nm to 730nm, and light in the specific wavelength range has a peak wavelength ina wavelength range of 585 nm to 615 nm or 610 nm to 730 nm.

(Additional Remark 10)

The medical image processing device, wherein the specific wavelengthrange includes a wavelength range where a light absorption coefficientin oxyhemoglobin is different from that in reduced hemoglobin, and lightin the specific wavelength range has a peak wavelength in a wavelengthrange where a light absorption coefficient in oxyhemoglobin is differentfrom that in reduced hemoglobin.

(Additional Remark 11)

The medical image processing device, wherein the specific wavelengthrange includes a wavelength range of 400±10 nm, 440±10 nm, 470±10 nm, or600 nm to 750 nm, and light in the specific wavelength range has a peakwavelength in a wavelength range of 400±10 nm, 440±10 nm, 470±10 nm, or600 nm to 750 nm.

(Additional Remark 12)

The medical image processing device, wherein the medical image is anin-vivo image of the inside of a living body, and the in-vivo image hasinformation of fluorescence emitted by fluorescent materials in theliving body.

(Additional Remark 13)

The medical image processing device, wherein the fluorescence isobtained from the application of excitation light, which has a peakwavelength in a range of 390 nm to 470 nm, to the inside of the livingbody.

(Additional Remark 14)

The medical image processing device, wherein the medical image is anin-vivo image of the inside of a living body, and the specificwavelength range is an infrared wavelength range.

(Additional Remark 15)

The medical image processing device, wherein the specific wavelengthrange includes a wavelength range of 790 nm to 820 nm or 905 nm to 970nm, and light in the specific wavelength range has a peak wavelength ina wavelength range of 790 nm to 820 nm or 905 nm to 970 nm.

(Additional Remark 16)

The medical image processing device, wherein a medical image acquisitionunit comprises a special light image acquisition unit that acquires aspecial light image having information about the specific wavelengthrange on the basis of a normal light image obtained from the applicationof light in a white-light wavelength range or light in a plurality ofwavelength ranges as the light in a white-light wavelength range, andthe medical image is the special light image.

(Additional Remark 17)

The medical image processing device, wherein a signal in the specificwavelength range is obtained by arithmetic operation based oninformation about colors of red, green, and blue (RGB) or cyan, magenta,and yellow (CMY) included in the normal light image.

(Additional Remark 18)

The medical image processing device further comprising: afeature-quantity-image generation unit generating a feature quantityimage from an arithmetic operation based on at least one of the normallight image that is obtained from the application of light in awhite-light wavelength range or light in a plurality of wavelengthranges as the light in a white-light wavelength range and the speciallight image that is obtained from the application of light in a specificwavelength range, wherein the medical image is the feature quantityimage.

(Additional Remark 19)

An endoscope apparatus comprising: the medical image processing deviceaccording to any one of Additional remarks 1 to 18; and an endoscopethat acquires an image from the application of at least one of light ina white-light wavelength range or light in the specific wavelengthrange.

(Additional Remark 20)

A diagnosis support apparatus comprising: the medical image processingdevice according to any one of Additional remarks 1 to 18.

(Additional Remark 21)

A medical service support apparatus comprising: the medical imageprocessing device according to any one of Additional remarks 1 to 18.

Others

The above-described image processing method may be configured as aprogram for causing a computer to realize each step, and anon-transitory recording medium such as a compact disk read-only memory(CD-ROM) in which the program is stored may be configured.

In the above-described embodiments, for example, the hardware structuresof processing units executing various kinds of processing of theprocessor device 16 are the following various processors. The variousprocessors include a central processing unit (CPU) as a general-purposeprocessor executing software (program) and functioning as variousprocessing units, a graphics processing unit (GPU) as a processorspecialized for image processing, a programmable logic device (PLD) as aprocessor of which the circuit configuration can be changed aftermanufacturing such as a field programmable gate array (FPGA), adedicated electrical circuit as a processor having a circuitconfiguration designed exclusively for executing a specific process suchas an application specific integrated circuit (ASIC).

One processing unit may be configured by one of the various processors,or configured by the same or different kinds of two or more processors(for example, combination of a plurality of FPGAs, combination of theCPU and the FPGA, combination of the CPU and the GPU, or the like). Inaddition, a plurality of processing units may be configured by oneprocessor. As an example where a plurality of processing units areconfigured by one processor, first, there is an aspect where oneprocessor is configured by a combination of one or more CPUs andsoftware as typified by a computer, such as a server and a client, andthis processor functions as a plurality of processing units. Second,there is an aspect where a processor fulfilling the functions of theentire system including a plurality of processing units by oneintegrated circuit (IC) chip as typified by a system on chip (SoC) orthe like is used. In this manner, various processing units areconfigured by using one or more of the various processors as hardwarestructures.

Furthermore, the hardware structures of these various processors aremore specifically electrical circuitry where circuit elements, such assemiconductor elements, are combined.

The technical scope of the invention is not limited to the scopedescribed in the above embodiments. The configurations and the like inthe embodiments can be appropriately combined between the embodiments ina range not departing from the gist of the invention.

EXPLANATION OF REFERENCES

-   -   10: endoscope system    -   12: endoscope    -   12A: insertion part    -   12B: operation part    -   12C: bendable part    -   12D: distal end part    -   12E: angle knob    -   13: mode switching switch    -   14: light source device    -   16: processor device    -   18: display unit    -   20: input unit    -   22A: first laser light source    -   22B: second laser light source    -   24: light source control unit    -   28A: optical fiber    -   28B: optical fiber    -   30: phosphor    -   32: diffusion member    -   34: imaging lens    -   36: imaging element    -   38: analog-to-digital conversion unit    -   40: imaging control unit    -   42: image processing unit    -   44: image acquisition unit    -   46: lesion region detection unit    -   46A: first detection unit    -   46B: second detection unit    -   46C: third detection unit    -   46D: fourth detection unit    -   46E: fifth detection unit    -   46F: sixth detection unit    -   46G: seventh detection unit    -   46H: eighth detection unit    -   48: positional information acquisition unit    -   50: position recognition unit    -   52: selection unit    -   54: lesion region detection control unit    -   56: medical image processing device    -   58: display control unit    -   60: storage control unit    -   62: storage unit    -   70: endoscope system    -   100: ultrasound diagnostic apparatus    -   102: ultrasound probe    -   104: transmission/reception control unit    -   106: transmission unit    -   108: reception unit    -   110: image processing unit    -   G_(E): image    -   G_(S): schematic diagram    -   L₀: irradiation light    -   L₁: light    -   L₁₁: excitation light    -   L₁₂: laser light    -   L₂: light    -   S1 to S6: processing of image diagnosis method

What is claimed is:
 1. An endoscope system comprising: an endoscopeconfigured to be inserted into a body cavity of a subject; and aprocessor configured to: acquire images at in-vivo positions of thesubject by sequentially capturing the images through the endoscope;acquire positional information indicating the in-vivo positions of theacquired images; select a detection unit corresponding to a positionindicated by the acquired positional information from aregion-of-interest detection unit configured to detect a region ofinterest in an input image; cause the selected detection unit to detecta region of interest in the acquired images; and cause a display todisplay the position indicated by the acquired positional information.2. The endoscope system according to claim 1, wherein the processor isfurther configured to cause the display to display a schematic diagramof the subject and a figure on the schematic diagram at the positionindicated by the acquired positional information.
 3. The endoscopesystem according to claim 2, wherein the processor is further configuredto cause the display to display one of the acquired images correspondingto the position indicated by the acquired positional information,together with the schematic diagram and the figure.
 4. The endoscopesystem according to claim 3, wherein the schematic diagram is of a lumenof the subject.
 5. The endoscope system according to claim 1, whereinthe processor is further configured to recognize the in-vivo positionsfrom the acquired images.
 6. The endoscope system according to claim 1,wherein the processor is further configured to receive the positionalinformation through a user's input.
 7. The endoscope system according toclaim 6, wherein: the endoscope is configured to be inserted from amouth or a nose of the subject; and the processor is configured toreceive the positional information indicating at least one of positionsof a pharynx, an esophagus, a stomach and a duodenum of the subject. 8.The endoscope system according to claim 6, wherein: the endoscope isconfigured to be inserted from an anus of the subject; and the processoris configured to receive the positional information indicating at leastone of positions of a rectum, a sigmoid colon, a descending colon, atransverse colon, an ascending colon, a cecum, an ileum and a jejunum ofthe subject.
 9. The endoscope system according to claim 1, wherein thepositional information is acquired by an endoscope insertion shapeobservation device or by irradiating the subject with X-rays from anoutside.
 10. The endoscope system according to claim 1, wherein theregion-of-interest detection unit includes a plurality of learnedmodels.
 11. The endoscope system according to claim 10, wherein thelearned models are models learned using different data sets,respectively.
 12. The endoscope system according to claim 11, whereinthe learned models are models learned using data sets including imagesof mucous membranes at different in-vivo positions, respectively. 13.The endoscope system according to claim 11, wherein the learned modelsare models learned using data sets including images captured atdifferent in-vivo positions, respectively.
 14. The endoscope systemaccording to claim 13, wherein: the processor is further configured torecognize the in-vivo positions from the acquired images by means of thelearned models; and the in-vivo positions include positions of a mouth,a pharynx, an esophagus, a stomach, and a duodenum of the subject. 15.The endoscope system according to claim 1, wherein the processor isconfigured to chronologically capture the images at the in-vivopositions.
 16. The endoscope system according to claim 15, wherein theprocessor is configured to capture the images at a fixed frame rate. 17.The endoscope system according to claim 1, further comprising a storage,wherein the processor is further configured to cause the storage tostore the acquired image containing the region of interest and thepositional information associated with each other.
 18. The endoscopesystem according to claim 1, wherein the region-of-interest detectionunit is configured to detect a lesion region as the region of interest.19. The endoscope system according to claim 1, wherein the processor isfurther configured to cause the display to display the positionalinformation.
 20. The endoscope system according to claim 1, wherein: theendoscope includes a camera; and the processor is configured to capturethe images through the camera.